Abstract
The medical and satellite images are mostly corrupted by a multiplicative granular noise called speckle noise which degrades the quality of the images captured by using medical imaging techniques and also Synthetic Aperture Radar images. It causes difficulties in image interpretation and this is mainly due to back scattered signals from the multiple targets. In medical field, the diagnosis of the tissues, bones and organs takes place by using imaging techniques. By using different imaging techniques, the medical images are captured and used for diagnosis. Different types of filtering techniques are proposed in the literature to remove the speckle noise in medical and satellite images. In this research paper different types of adaptive filters and its modifications are proposed and compared. The filters like modified lee filter, modified Edge Enhanced lee filter, modified fast bilateral filter and Modified Particle Swarm Optimization based despeckling algorithm. The results are verified for both simulated images and real medical images and also for Synthetic Aperture Radar images. The results are compared in terms of both objective and subjective analysis for simulated and real medical images. The simulation is done using MATLAB R2013 and the visual qualities of the images are analyzed for varying noise densities.
Highlights
Speckle noise is a type of multiplicative noise which corrupts SAR images, ultrasound images etc.The noises in medical images occur due to the reflected waves from the targeted organs which are captured by using different imaging devices
The results are compared in terms of both objective and subjective analysis for simulated and real medical images
The results are compared in terms of both Quantitative and Qualitative measures, in which the optimization based Edge Enhanced Lee filter gives good results in terms of Peak to Signal Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM)
Summary
Speckle noise is a type of multiplicative noise which corrupts SAR images, ultrasound images etc. The noises in medical images occur due to the reflected waves from the targeted organs which are captured by using different imaging devices. The different imaging devices used for capturing medical devices is Ultrasound scanning, Magnetic resonance imaging, X- ray imaging and Computer tomography imaging. The filters used for the removal of speckle noise are classified as non adaptive filters and adaptive filters. The speckle denoising algorithm follows Homomorphic filtering, which converts the multiplicative noise into additive noise and the noise reduction is done. For the removal of additional noises there are different methods like least mean squares, averaging filter, wiener filtering, wavelet based denoising methods are adopted (Stian Solbo & Torbjorn Eltoft 2008)
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